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Prepare for encoding of endpoint and selector indexes in non-linear order

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This change makes the compression scheme more flexible.

Explanation:
In the original scheme, indexes are encoded in linear order, which means that each index uses the previously encoded index for prediction. However, more sophisticated schemes might require arbitrary references into the stream of already encoded indexes. For this reason, Zeng function has been modified to accept the ordering histogram as an input, instead of the linear array of indexes. Note that Zeng function itself does not rely on the indexes being encoded in linear order.

Testing:
The modified algorithm has been tested on the Kodak test set using 64-bit build with default settings (running on Windows 10, i7-4790, 3.6GHz). All the decompressed test images are identical to the images being compressed and decompressed using original version of Crunch.

[Compressing Kodak set without mipmaps]
Original: 1582222 bytes / 28.867 sec
Modified: 1570534 bytes / 28.524 sec
Improvement: 0.74% (compression ratio) / 1.19% (compression time)

[Compressing Kodak set with mipmaps]
Original: 2065243 bytes / 37.001 sec
Modified: 2051509 bytes / 36.388 sec
Improvement: 0.67% (compression ratio) / 1.66% (compression time)
This commit is contained in:
Alexander Suvorov
2017-04-28 11:32:14 +02:00
parent 8cc5f19ae5
commit 19f05aadbc
4 changed files with 72 additions and 125 deletions
Download Patch File Download Diff File Expand all files Collapse all files
crnlib/crn_comp.cpp
+52 -12
View File
@@ -1315,6 +1315,7 @@ struct optimize_color_endpoint_codebook_params {
crnlib::vector<uint>* m_pTrial_color_endpoint_remap;
uint m_iter_index;
uint m_max_iter_index;
hist_type* xhist;
};
void crn_comp::optimize_color_endpoint_codebook_task(uint64 data, void* pData_ptr) {
@@ -1328,8 +1329,7 @@ void crn_comp::optimize_color_endpoint_codebook_task(uint64 data, void* pData_pt
create_zeng_reorder_table(
m_hvq.get_color_endpoint_codebook_size(),
m_endpoint_indices[cColor].size(),
&m_endpoint_indices[cColor][0],
*pParams->xhist,
*pParams->m_pTrial_color_endpoint_remap,
pParams->m_iter_index ? color_endpoint_similarity_func : NULL,
&m_hvq,
@@ -1362,11 +1362,22 @@ bool crn_comp::optimize_color_endpoint_codebook(crnlib::vector<uint>& remapping)
crnlib::vector<uint> trial_color_endpoint_remaps[cMaxEndpointRemapIters + 1];
uint n = m_hvq.get_color_endpoint_codebook_size();
hist_type xhist(n * n);
for (uint i = 0; i < m_endpoint_indices[cColor].size(); i++) {
const int prev_val = (i > 0) ? m_endpoint_indices[cColor][i - 1] : -1;
const int cur_val = m_endpoint_indices[cColor][i];
const int next_val = (i < (m_endpoint_indices[cColor].size() - 1)) ? m_endpoint_indices[cColor][i + 1] : -1;
update_hist(xhist, cur_val, prev_val, n);
update_hist(xhist, cur_val, next_val, n);
}
for (uint i = 0; i <= cMaxEndpointRemapIters; i++) {
optimize_color_endpoint_codebook_params* pParams = crnlib_new<optimize_color_endpoint_codebook_params>();
pParams->m_iter_index = i;
pParams->m_max_iter_index = cMaxEndpointRemapIters;
pParams->m_pTrial_color_endpoint_remap = &trial_color_endpoint_remaps[i];
pParams->xhist = &xhist;
m_task_pool.queue_object_task(this, &crn_comp::optimize_color_endpoint_codebook_task, 0, pParams);
}
@@ -1418,6 +1429,7 @@ struct optimize_color_selector_codebook_params {
crnlib::vector<uint>* m_pTrial_color_selector_remap;
uint m_iter_index;
uint m_max_iter_index;
hist_type* xhist;
};
void crn_comp::optimize_color_selector_codebook_task(uint64 data, void* pData_ptr) {
@@ -1430,8 +1442,7 @@ void crn_comp::optimize_color_selector_codebook_task(uint64 data, void* pData_pt
float f = pParams->m_iter_index / static_cast<float>(pParams->m_max_iter_index - 1);
create_zeng_reorder_table(
m_hvq.get_color_selector_codebook_size(),
m_selector_indices[cColor].size(),
&m_selector_indices[cColor][0],
*pParams->xhist,
*pParams->m_pTrial_color_selector_remap,
pParams->m_iter_index ? color_selector_similarity_func : NULL,
(void*)&m_hvq.get_color_selectors_vec(),
@@ -1471,11 +1482,22 @@ bool crn_comp::optimize_color_selector_codebook(crnlib::vector<uint>& remapping)
crnlib::vector<uint> trial_color_selector_remaps[cMaxSelectorRemapIters + 1];
uint n = m_hvq.get_color_selector_codebook_size();
hist_type xhist(n * n);
for (uint i = 0; i < m_selector_indices[cColor].size(); i++) {
const int prev_val = (i > 0) ? m_selector_indices[cColor][i - 1] : -1;
const int cur_val = m_selector_indices[cColor][i];
const int next_val = (i < (m_selector_indices[cColor].size() - 1)) ? m_selector_indices[cColor][i + 1] : -1;
update_hist(xhist, cur_val, prev_val, n);
update_hist(xhist, cur_val, next_val, n);
}
for (uint i = 0; i <= cMaxSelectorRemapIters; i++) {
optimize_color_selector_codebook_params* pParams = crnlib_new<optimize_color_selector_codebook_params>();
pParams->m_iter_index = i;
pParams->m_max_iter_index = cMaxSelectorRemapIters;
pParams->m_pTrial_color_selector_remap = &trial_color_selector_remaps[i];
pParams->xhist = &xhist;
m_task_pool.queue_object_task(this, &crn_comp::optimize_color_selector_codebook_task, 0, pParams);
}
@@ -1530,10 +1552,10 @@ bool crn_comp::optimize_color_selector_codebook(crnlib::vector<uint>& remapping)
}
struct optimize_alpha_endpoint_codebook_params {
crnlib::vector<uint>* m_pAlpha_indices;
crnlib::vector<uint>* m_pTrial_alpha_endpoint_remap;
uint m_iter_index;
uint m_max_iter_index;
hist_type* xhist;
};
void crn_comp::optimize_alpha_endpoint_codebook_task(uint64 data, void* pData_ptr) {
@@ -1547,8 +1569,7 @@ void crn_comp::optimize_alpha_endpoint_codebook_task(uint64 data, void* pData_pt
create_zeng_reorder_table(
m_hvq.get_alpha_endpoint_codebook_size(),
pParams->m_pAlpha_indices->size(),
&(*pParams->m_pAlpha_indices)[0],
*pParams->xhist,
*pParams->m_pTrial_alpha_endpoint_remap,
pParams->m_iter_index ? alpha_endpoint_similarity_func : NULL,
&m_hvq,
@@ -1587,12 +1608,22 @@ bool crn_comp::optimize_alpha_endpoint_codebook(crnlib::vector<uint>& remapping)
crnlib::vector<uint> trial_alpha_endpoint_remaps[cMaxEndpointRemapIters + 1];
uint n = m_hvq.get_alpha_endpoint_codebook_size();
hist_type xhist(n * n);
for (uint i = 0; i < alpha_indices.size(); i++) {
const int prev_val = (i > 0) ? alpha_indices[i - 1] : -1;
const int cur_val = alpha_indices[i];
const int next_val = (i < (alpha_indices.size() - 1)) ? alpha_indices[i + 1] : -1;
update_hist(xhist, cur_val, prev_val, n);
update_hist(xhist, cur_val, next_val, n);
}
for (uint i = 0; i <= cMaxEndpointRemapIters; i++) {
optimize_alpha_endpoint_codebook_params* pParams = crnlib_new<optimize_alpha_endpoint_codebook_params>();
pParams->m_pAlpha_indices = &alpha_indices;
pParams->m_iter_index = i;
pParams->m_max_iter_index = cMaxEndpointRemapIters;
pParams->m_pTrial_alpha_endpoint_remap = &trial_alpha_endpoint_remaps[i];
pParams->xhist = &xhist;
m_task_pool.queue_object_task(this, &crn_comp::optimize_alpha_endpoint_codebook_task, 0, pParams);
}
@@ -1641,10 +1672,10 @@ bool crn_comp::optimize_alpha_endpoint_codebook(crnlib::vector<uint>& remapping)
}
struct optimize_alpha_selector_codebook_params {
crnlib::vector<uint>* m_pAlpha_indices;
crnlib::vector<uint>* m_pTrial_alpha_selector_remap;
uint m_iter_index;
uint m_max_iter_index;
hist_type* xhist;
};
void crn_comp::optimize_alpha_selector_codebook_task(uint64 data, void* pData_ptr) {
@@ -1657,8 +1688,7 @@ void crn_comp::optimize_alpha_selector_codebook_task(uint64 data, void* pData_pt
float f = pParams->m_iter_index / static_cast<float>(pParams->m_max_iter_index - 1);
create_zeng_reorder_table(
m_hvq.get_alpha_selector_codebook_size(),
pParams->m_pAlpha_indices->size(),
&(*pParams->m_pAlpha_indices)[0],
*pParams->xhist,
*pParams->m_pTrial_alpha_selector_remap,
pParams->m_iter_index ? alpha_selector_similarity_func : NULL,
(void*)&m_hvq.get_alpha_selectors_vec(),
@@ -1703,12 +1733,22 @@ bool crn_comp::optimize_alpha_selector_codebook(crnlib::vector<uint>& remapping)
crnlib::vector<uint> trial_alpha_selector_remaps[cMaxSelectorRemapIters + 1];
uint n = m_hvq.get_alpha_selector_codebook_size();
hist_type xhist(n * n);
for (uint i = 0; i < alpha_indices.size(); i++) {
const int prev_val = (i > 0) ? alpha_indices[i - 1] : -1;
const int cur_val = alpha_indices[i];
const int next_val = (i < (alpha_indices.size() - 1)) ? alpha_indices[i + 1] : -1;
update_hist(xhist, cur_val, prev_val, n);
update_hist(xhist, cur_val, next_val, n);
}
for (uint i = 0; i <= cMaxSelectorRemapIters; i++) {
optimize_alpha_selector_codebook_params* pParams = crnlib_new<optimize_alpha_selector_codebook_params>();
pParams->m_pAlpha_indices = &alpha_indices;
pParams->m_iter_index = i;
pParams->m_max_iter_index = cMaxSelectorRemapIters;
pParams->m_pTrial_alpha_selector_remap = &trial_alpha_selector_remaps[i];
pParams->xhist = &xhist;
m_task_pool.queue_object_task(this, &crn_comp::optimize_alpha_selector_codebook_task, 0, pParams);
}